Výsledky vyhľadávania - Quantile regression AND single-loop algorithm

Smoothing ADMM for Sparse-Penalized Quantile Regression With Non-Convex Penalties

Autori: Mirzaeifard, Reza Kumar Dasanadoddi Venkategowda, Naveen Gogineni, Vinay Chakravarthi a ďalší

Zdroj: IEEE Open Journal of Signal Processing. 5:213-228

Predmety: Convergence, Smoothing methods, Optimization, Signal processing algorithms, Convex functions, Signal processing, Prediction algorithms, Quantile regression, non-smooth and non-convex penalties, ADMM, sparse learning

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-200383
https://doi.org/10.1109/OJSP.2023.3344395

A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression

Autori: Yu, Liqun Lin, Nan Wang, Lan

Zdroj: Journal of Computational and Graphical Statistics, 2017 Dec 01. 26(4), 935-939.

Prístupová URL adresa: https://www.jstor.org/stable/44862022

A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression

Autori: Nan Lin Liqun Yu Lan Wang

Zdroj: Journal of Computational and Graphical Statistics. 26:935-939

Predmety: 0101 mathematics, 16. Peace & justice, 01 natural sciences

Prístupová URL adresa: https://experts.umn.edu/en/publications/a-parallel-algorithm-for-large-scale-nonconvex-penalized-quantile
https://www.tandfonline.com/doi/abs/10.1080/10618600.2017.1328366
https://amstat.tandfonline.com/doi/full/10.1080/10618600.2017.1328366
https://core.ac.uk/display/149386811

Smoothing ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties

Autori: Mirzaeifard, Reza Venkategowda, Naveen K. D. Gogineni, Vinay Chakravarthi a ďalší

Témy: Statistics - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2309.03094

Gaining Outlier Resistance With Progressive Quantiles: Fast Algorithms and Theoretical Studies.

Autori: She, Yiyuan Wang, Zhifeng Shen, Jiahui

Zdroj: Journal of the American Statistical Association; Sep2022, Vol. 117 Issue 539, p1282-1295, 14p

Predmety: QUANTILES, ALGORITHMS, INFERENTIAL statistics, MATHEMATICAL statistics, RESAMPLING (Statistics), QUANTILE regression

Screen then select: a strategy for correlated predictors in high-dimensional quantile regression.

Autori: Jiang, Xuejun Liang, Yakun Wang, Haofeng

Zdroj: Statistics & Computing; Jun2024, Vol. 34 Issue 3, p1-31, 31p

Belief reliability-based design optimization method with quantile index under epistemic uncertainty.

Autori: Yubing Chen Meilin Wen Qingyuan Zhang a ďalší

Zdroj: Maintenance & Reliability / Eksploatacja i Niezawodność; 2023, Vol. 25 Issue 2, p1-15, 15p

Predmety: EPISTEMIC uncertainty, QUANTILE regression, ENGINEERING reliability theory, PRODUCT design

Distributed Quantile Regression Analysis and a Group Variable Selection Method

Autori: Yu, Liqun

Predmety: Statistics and Probability, penalization, admm, quantile regression, big data, divide-and-combine, group variable selection

Popis súboru: application/pdf

Prístupová URL adresa: https://openscholarship.wustl.edu/cgi/viewcontent.cgi?article=2631&context=art_sci_etds
https://openscholarship.wustl.edu/art_sci_etds/1604/

Quantile-based optimization under uncertainties using adaptive Kriging surrogate models.

Autori: Moustapha, Maliki Sudret, Bruno Bourinet, Jean-Marc a ďalší

Zdroj: Structural & Multidisciplinary Optimization; Dec2016, Vol. 54 Issue 6, p1403-1421, 19p

Predmety: QUANTILE regression, MATHEMATICAL optimization, INDUSTRIAL design, PROBABILITY theory, KRIGING

A short-term load forecasting framework for air conditioning system based on model stacking.

Autori: Liu, Tianjie Jiao, Wenling Huang, Zhiwei a ďalší

Zdroj: Scientific Reports; 10/22/2025, Vol. 15 Issue 1, p1-17, 17p

Predmety: AIR conditioning, MACHINE learning, FEATURE selection, PREDICTION models, ESTIMATION theory, DEMAND forecasting, ENSEMBLE learning

Heterogeneous Functional Regression for Subgroup Analysis.

Autori: Zhou, Yeqing Jiang, Fei

Zdroj: Journal of Computational & Graphical Statistics; Jul-Sep2025, Vol. 34 Issue 3, p872-883, 12p

Predmety: SUBGROUP analysis (Experimental design), HETEROGENEITY, ALZHEIMER'S patients, MATHEMATICAL regularization, STATISTICS, PARAMETER estimation, FUNCTIONAL analysis, INDEPENDENT variables

An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions.

Autori: Algwil, Ahmed Ramdan Almaqtouf Khalifa, Wagdi M. S.

Zdroj: Scientific Reports; 4/8/2025, Vol. 15 Issue 1, p1-24, 24p

Predmety: EXTREME learning machines, MACHINE learning, STANDARD deviations, OPTIMIZATION algorithms, FOREIGN investments, EVOLUTIONARY computation

A single-loop Kriging model coupled with cross-entropy importance sampling for time-variant reliability analysis of rare events.

Autori: Pan, Chenrong Zha, Congyi Tang, Jianghua

Zdroj: Journal of the Brazilian Society of Mechanical Sciences & Engineering; Sep2025, Vol. 47 Issue 9, p1-12, 12p

Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method.

Autori: Wang, Yingdong Xing, Chen Yao, Leihua

Zdroj: Applied Sciences (2076-3417); Nov2024, Vol. 14 Issue 22, p10527, 19p

Predmety: FAILURE mode & effects analysis, RANDOM variables, SEARCH algorithms, STRUCTURAL design, SENSITIVITY analysis

A linearization for stable and fast geographically weighted Poisson regression.

Autori: Murakami, Daisuke Tsutsumida, Narumasa Yoshida, Takahiro a ďalší

Zdroj: International Journal of Geographical Information Science; Aug2023, Vol. 37 Issue 8, p1818-1839, 22p

Predmety: CRIME analysis, REGRESSION analysis, POISSON'S equation, CRIME statistics

An efficient algorithm for time-dependent failure credibility by combining adaptive single-loop Kriging model with fuzzy simulation.

Autori: Jiang, Xia Lu, Zhenzhou

Zdroj: Structural & Multidisciplinary Optimization; Sep2020, Vol. 62 Issue 3, p1025-1039, 15p

Predmety: KRIGING, ALGORITHMS, PROCESS optimization, SIMULATION methods & models, SAFETY

Reliability-based design optimization: a state-of-the-art review of its methodologies, applications, and challenges.

Autori: Hu, Weifei Cheng, Sichuang Yan, Jiquan a ďalší

Zdroj: Structural & Multidisciplinary Optimization; Sep2024, Vol. 67 Issue 9, p1-31, 31p

主动学习自适应 PC-Kriging 在结构可靠性分析中的应用. (Chinese)

Alternate Title: Application of Active Learning Adaptive PC-Kriging in Structural Reliability Analysis. (English)

Autori: 代俊男 周金宇

Zdroj: Machine Tool & Hydraulics; Aug2025, Vol. 53 Issue 16, p51-57, 7p

Predmety: K-means clustering, PARALLEL programming, FAILURE (Psychology), STRUCTURAL reliability, POINT set theory, KRIGING

Accelerometer-Based Pavement Classification for Vehicle Dynamics Analysis Using Neural Networks.

Autori: Surblys, Vytenis Kozłowski, Edward Matijošius, Jonas a ďalší

Zdroj: Applied Sciences (2076-3417); Nov2024, Vol. 14 Issue 21, p10027, 26p

Predmety: ARTIFICIAL neural networks, PAVEMENTS, STRAINS & stresses (Mechanics), MOTOR vehicle springs & suspension, REGRESSION analysis

Analysis of Instantaneous Energy Consumption and Recuperation Based on Measurements from SORT Runs.

Autori: Kozłowski, Edward Zimakowska-Laskowska, Magdalena Dudziak, Agnieszka a ďalší

Zdroj: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p1681, 25p

Predmety: GREENHOUSE gases, ENERGY management, K-nearest neighbor classification, CITY traffic, ENERGY consumption